Overview
This is a narrative review published in Frontiers in Nutrition (received 13 June 2024; published 29 July 2024) by researchers from the Department of Personnel Management, Zhejiang Center for Disease Control and Prevention, Hangzhou, China. The paper reviews the bidirectional metabolic interactions between 10 common heavy metals and the gut microbiota, covering both toxic heavy metals (arsenic, mercury, lead, and cadmium) and essential trace elements (copper, manganese, and iron) as well as conditionally essential or intermediate-toxicity elements (chromium, nickel, and silicon). The central argument is that the gut microbiota functions simultaneously as a target of heavy metal toxicity and as a modulator of heavy metal absorption, biotransformation, and excretion. No primary measurements are reported; all quantitative claims are drawn from cited literature, primarily rodent and fish studies, one human epidemiologic cohort, and one occupational-exposure study.
Study design
This is a narrative (non-systematic) literature review. No PRISMA protocol is stated. No explicit search strategy, database list, date range, or inclusion and exclusion criteria are reported. The authors are staff at the Zhejiang Center for Disease Control and Prevention; no external funding is declared; no conflict of interest is stated. The review is organized by metal class (toxic heavy metals in Section 3, essential trace elements in Section 4, and intermediate elements in Section 4.4) and within each class by individual metal. The paper presents three summary tables (Table 1 for toxic metals, Table 2 for essential trace elements, and Table 3 for other trace elements) listing experiment model, effect on gut microbiota composition, effect on gut metabolites and barrier integrity, outcome, and reference. The number of primary studies synthesized per metal ranges from roughly 5 to 15; the total reference list contains 152 citations.
Samples
No primary samples. The review synthesizes published experiments on animal models (mice, rats, fish including zebrafish and common carp, crayfish, bees, geese, budgerigars, and tilapia), one human epidemiologic cohort study on multi-metal exposure and gut microbiota diversity, and one occupational-exposure study of nickel workers. Sample sizes for the underlying studies are not tabulated in the review.
Methods
This is a review article. No analytical methods, instruments, detection limits, certified reference materials, or recovery data are reported by the authors. The methods for the underlying primary studies are described qualitatively in Section 2.3 (“The methods for determining the relationship between heavy metals and gut microbiota”): approaches include in vivo rodent and fish experiments, oral antibiotic-treated and germ-free mouse models, in vitro gut fermentation models, and simulated human intestinal microbial ecosystem (SHIME) models. 16S rRNA amplicon sequencing and metabolomics (fecal and serum) are the primary analytical platforms cited in the reviewed studies.
No instrument reported; not applicable (review).
Limit of detection / limit of quantification: not reported; not applicable (review).
Certified reference material and recovery: not reported; not applicable (review).
Results
The review’s principal findings are organized below by metal class, drawing directly from Sections 3 and 4 and Tables 1 through 3.
Toxic heavy metals (Table 1)
Arsenic (As). Arsenic exposure alters gut microbiota composition in a broadly consistent direction across animal models: increased Bacteroidetes, Alkalitalea, and Akkermansia; decreased Firmicutes, Lachnospiraceae, and Ruminococcaceae. The gut microbiota influences arsenic speciation: conventional mice display lower total arsenic and lower MMA/DMA ratios in urine than dysbiotic mice, indicating that an intact microbiota promotes arsenic methylation and excretion. Arsenic disrupts bile acid metabolism by modulating farnesoid X receptor (FXR), pregnane X receptor (PXR), vitamin D3 receptor (VDR), constitutive androstane receptor (CAR), and G protein-coupled bile acid receptor 1 (TGR5) expression (reference 57 in the paper). The tilapia experiment (reference 56) showed that gut bacteria convert As(V) to As(III) and organoarsenicals, including less-toxic organic forms. Methylated trivalent arsenic species (MMAIII and DMAIII) reduce glucose-stimulated insulin secretion by impairing calcium influx, contributing to diabetes risk.
Mercury (Hg). At the phylum level, inorganic mercury (Hg2+) increased Firmicutes, Bacteroidetes, and Actinobacteria and decreased Proteobacteria and Verrucomicrobia in mice (reference 62). Methylmercury (MeHg) exposure increased Proteobacteria and Bacteroidetes and decreased Desulfobacterota. The gut microbiota demethylates MeHg to less toxic, less soluble inorganic forms; antibiotic-treated and germ-free mice show significantly reduced methylmercury excretion and higher MeHg accumulation in blood and tissues. MeHg disrupts the gut-brain axis by altering neurotransmitter-related metabolites (gamma-aminobutyric acid (GABA), serotonin, dopamine, and creatine) and perturbs the gut-liver axis (reference 62). Hg concentrations are significantly associated with Parabacteroides and Oscillospira abundance in the guts of children with autism (reference 89 in the paper).
Lead (Pb) and cadmium (Cd). Lead reduces alpha-diversity and richness of gut microbiota in mice (reference 29 in the paper) and disrupts vitamin E, bile acid, nitrogen, energy, and oxidative stress metabolic pathways. In a human epidemiologic study (reference 39 in the paper), increasing urinary lead levels were associated with increases in microbial alpha-diversity and richness, with elevated Succinivibrionaceae and Gammaproteobacteria. Pb exposure in high-fat diet mice increases the Firmicutes/Bacteroidetes ratio and abundance of Erysipelotrichaceae, while decreasing Rikenellaceae, Akkermansiaceae, and Ruminococcaceae, and reducing short-chain fatty acid (SCFA) levels, leading to impaired glucose homeostasis and intestinal inflammation (reference 68 in the paper). Prenatal Pb exposure decreases Akkermansia and increases Desulfovibrio, contributing to adult weight gain in male mice.
Cadmium alters microbiota composition and metabolic profiles in both rodent and invertebrate models. In freshwater crayfish, Cd exposure increases amino acid, carbohydrate, energy, and nucleotide metabolism while decreasing lipid metabolism (reference 13 in the paper). In mice, Cd increases Helicobacter and Campylobacter, activates glutamate metabolism, and promotes mammary tumor formation (reference 69 in the paper). In adolescent rats, Cd exposure reduces Prevotellaceae and Lachnospiraceae, increases Escherichia coli and Shigella, elevates serum triglycerides and LPS, and upregulates IL-1beta, IL-6, and TNF-alpha gene expression in liver, kidney, and ovary (reference 71 in the paper).
Joint multi-metal exposure: one epidemiologic cohort study (reference 42 in the paper) on long-term exposure to As, Cd, Cu, Pb, and Zn found increased relative abundances of Lachnospiraceae, Eubacterium eligens, Ruminococcaceae UGG-014, and Bacteroides and decreased Prevotella 9. Gender differences were observed, with greater richness and evenness in men in polluted areas.
Essential trace elements (Table 2)
Copper (Cu). Excess Cu has dose-dependent effects on gut microbiota in Sprague-Dawley rats: it reduces Firmicutes and Bacteroidetes and decreases Lactobacillus, Bifidobacterium, and Romboutsia (reference 102 in the paper). In juvenile common carp, Cu exposure decreased SCFA-producing bacteria including Blautia, Faecalibacterium, Roseburia, Ruminococcus, and Lachnospiraceae. Dietary Cu (120 and 240 mg/kg) elevated serum TNF-alpha in rats. Organic and inorganic Cu sources had distinct effects on cecal microbiota in rabbits.
Manganese (Mn). Excess Mn (15 mg/kg/day by gavage for 30 days in rats) decreases Prevotellaceae, Lachnospiraceae, and Lactobacillaceae and alters serotonin, deoxycholic acid, beta-hydroxybutyrate, and uric acid metabolism (reference 107 in the paper). Mn exposure in mice showed gender-specific effects: females showed decreased Firmicutes and increased Bacteroidetes; males showed the opposite pattern. Fecal microbiota transplantation from normal rats into Mn-exposed rats alleviated Mn-induced neurotoxicity (reference 109 in the paper). Supranutritional Mn (30 mg/kg, 10 weeks) in laying geese increased Prevotellaceae, Bacteroidetes, and Ruminococcaceae, reduced Streptococcaceae, and improved hatchability and eggshell thickness (reference 108 in the paper).
Iron (Fe). Iron deficiency in pigs increased volatile fatty acids (acetate, propionate, and butyrate) in the large intestine and increased Bifidobacterium, Dialister, and Prevotella while decreasing Bacteroides, Clostridium, and Ruminococcaceae (reference 113 in the paper). Low-iron diet in pigs increased Lactobacillus, decreased Escherichia coli-Shigella, and reduced TNF-alpha (reference 111 in the paper). Iron overload in mice reduced Akkermansia, Bifidobacterium, and Lactobacillus while increasing pathogenic taxa, and decreased anti-inflammatory metabolites including alpha-tocopherol; iron overload exacerbated colitis by activating ferroptosis of colonic cells (reference 112 in the paper). Excess iron in growth-restricted rats increased 3-hydroxybutyrate and decreased several amino acids in plasma and liver, adversely affecting cognitive development (reference 114 in the paper).
Intermediate and conditionally essential elements (Table 3)
Chromium (Cr). Cr3+ is an essential cofactor that at 0.4 mg/kg supplementation in heat-stressed broilers improved insulin resistance and altered gut microflora structure (reference 133 in the paper). Cr6+ is toxic. Short-term Cr6+ exposure in grouper fish reduced intestinal microbial diversity; Proteobacteria, Firmicutes, Actinobacteria, Bacteroidetes, and Cyanobacteria were major phyla. In zebrafish larvae, Cr6+ exposure decreased Proteobacteria and increased Actinobacteria, disturbed cholesterol metabolism via primary and secondary bile acid pathways, reduced acetylcholinesterase activity, and reduced locomotor behavior (reference 135 in the paper). Cr6+ in DMH-induced colorectal cancer mice promoted tumor formation and caused weight loss (reference 136 in the paper). In Bufo gargarizans tadpoles, Cr6+ decreased gut microbial diversity and increased risk of opportunistic pathogen infection (reference 137 in the paper).
Nickel (Ni). Long-term occupational Ni exposure in workers decreased Lactobacillus, unclassified Lachnospiraceae, and Blautia while increasing Parabacteroides and Escherichia-Shigella; purine degradation was impaired and primary bile acid biosynthesis was upregulated. In mice, Ni exposure significantly promoted hyperuricemia and systemic inflammation. Oral 400 microM NiSO4 in mice was non-toxic to body weight but altered gut microbiota composition (reference 141 in the paper). A low-nickel diet improved intestinal dysbiosis in patients with systemic nickel allergy syndrome (SNAS), with probiotic supplementation further restoring gut flora (reference 142 in the paper). Chronic combined Cr6+-Ni exposure showed an antagonistic effect: compared with single-metal exposure, combined exposure alleviated intestinal barrier damage and the inflammatory response (reference 143 in the paper).
Silicon (Si). Drinking silicon-containing water increased Weissella paramesenteroides, Lactobacillus reuteri, and Lactobacillus murinus, decreased Staphylococcus aureus, and inhibited gastric mucosal damage caused by gastric juice accumulation (reference 147 in the paper). SiO2 nanoparticles given orally increased Firmicutes and Patescibacteria, causing spatial learning and memory impairment and locomotor inhibition via a gut-brain axis mechanism (reference 148 in the paper). Time-specific silica exposure affected serum metabolites and gut microbiota in a duration-dependent pattern and may mediate silica-induced lung injury (reference 149 in the paper).
Evidence fitness
This source supports contextual and mechanistic claims only. It is a narrative review with no primary contamination measurements. All quantitative and taxonomic claims are drawn from secondary sources; no primary data are independently extracted or verified by the review authors. The source is appropriate for:
- Background citations on the bidirectional gut microbiota-heavy metal interaction framework.
- Mechanistic statements about gut microbial biotransformation of arsenic, mercury, and other metals.
- Contextual claims about microbial taxa consistently associated with heavy metal exposure (Lactobacillus and Bifidobacterium decrease; Proteobacteria increase; Akkermansia decrease with lead and cadmium).
- Discussion of the gut microbiome as a mediator of internal dose and metal toxicity, relevant to population-level exposure variability.
This source does not support contamination profile values, occurrence percentiles, regulatory limit derivations, or any food-matrix quantitative claim for any ingredient or product page.
Limitations (as reported or inferable)
The review does not state a systematic search protocol; selection bias toward positive-finding studies cannot be excluded. The majority of underlying studies used animal models (rodents and fish); human data are limited to two studies (one epidemiologic cohort, one occupational). Most underlying studies examined a single metal; real-world exposure involves simultaneous multi-metal mixtures. Gender is identified as a specific modifying variable for gut microbiota structure and heavy metal response, but most animal studies did not examine both sexes. Dose, duration, chemical species, bioavailability, and route of administration vary substantially across reviewed studies, limiting cross-study generalization. The review does not provide information on whether the animals in the reviewed studies were exposed via diet, drinking water, or gavage, or what doses correspond to realistic dietary exposures in humans.
Regulatory context
No regulatory context is discussed in the paper. The paper does not reference EU, FDA, Codex, or other regulatory limits for any metal. The focus is entirely on mechanistic biology, not food-safety standards.
Implications
- Certification: Background context for the HMTc scientific rationale. The microbiota-mediator framework supports the argument that internal dose from dietary heavy metal ingestion depends on gut microbial composition and cannot be fully predicted from intake alone. This reinforces precautionary certification approaches.
- Microbiome: Comprehensive review for metals-microbiota-health-outcomes triangulation. The paper’s Tables 1 through 3 are a useful structured summary of taxonomic shifts across 10 metals. A candidate for the microbiome/metals-microbiota-bidirectional-axis synthesis page and for WikiBiome federation.
- Courses: Useful for teaching the bidirectional interaction framework in dietary toxicology and the gut-brain and gut-liver axis sections involving methylmercury and lead.
- App: No contamination profile changes warranted; no food-matrix measurements reported.
Related evidence
- Lead
- Cadmium
- Arsenic
- Mercury
- Nickel
- Chromium
- Copper
- Iron
- Manganese
- microbiome/metals-microbiota-bidirectional-axis
Update history
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